Merge remote-tracking branch 'origin/master' into update-district-heating-cops

scripts/add_electricity.py

@@ -852,7 +852,7 @@ if __name__ == "__main__":
         fuel_price = pd.read_csv(
             snakemake.input.fuel_price, index_col=0, header=0, parse_dates=True
         )
-        fuel_price = fuel_price.reindex(n.snapshots).fillna(method="ffill")
+        fuel_price = fuel_price.reindex(n.snapshots).ffill()
     else:
         fuel_price = None
 

scripts/build_retro_cost.py

@@ -890,7 +890,7 @@ def calculate_gain_utilisation_factor(heat_transfer_perm2, Q_ht, Q_gain):
     Calculates gain utilisation factor nu.
     """
     # time constant of the building tau [h] = c_m [Wh/(m^2K)] * 1 /(H_tr_e+H_tb*H_ve) [m^2 K /W]
-    tau = c_m / heat_transfer_perm2.T.groupby(axis=1).sum().T
+    tau = c_m / heat_transfer_perm2.groupby().sum()
     alpha = alpha_H_0 + (tau / tau_H_0)
     # heat balance ratio
     gamma = (1 / Q_ht).mul(Q_gain.sum(axis=1), axis=0)

scripts/cluster_gas_network.py

@@ -58,6 +58,9 @@ def build_clustered_gas_network(df, bus_regions, length_factor=1.25):
     # drop pipes within the same region
     df = df.loc[df.bus1 != df.bus0]
 
+    if df.empty:
+        return df
+
     # recalculate lengths as center to center * length factor
     df["length"] = df.apply(
         lambda p: length_factor

scripts/make_summary_perfect.py

@@ -631,7 +631,7 @@ def calculate_co2_emissions(n, label, df):
     weightings = n.snapshot_weightings.generators.mul(
         n.investment_period_weightings["years"]
         .reindex(n.snapshots)
-        .fillna(method="bfill")
+        .bfill()
         .fillna(1.0),
         axis=0,
     )

scripts/plot_validation_electricity_production.py

@@ -70,7 +70,7 @@ if __name__ == "__main__":
     optimized = optimized[["Generator", "StorageUnit"]].droplevel(0, axis=1)
     optimized = optimized.rename(columns=n.buses.country, level=0)
     optimized = optimized.rename(columns=carrier_groups, level=1)
-    optimized = optimized.groupby(axis=1, level=[0, 1]).sum()
+    optimized = optimized.T.groupby(level=[0, 1]).sum().T
 
     data = pd.concat([historic, optimized], keys=["Historic", "Optimized"], axis=1)
     data.columns.names = ["Kind", "Country", "Carrier"]

scripts/prepare_network.py

@@ -137,9 +137,7 @@ def add_emission_prices(n, emission_prices={"co2": 0.0}, exclude_co2=False):
 def add_dynamic_emission_prices(n):
     co2_price = pd.read_csv(snakemake.input.co2_price, index_col=0, parse_dates=True)
     co2_price = co2_price[~co2_price.index.duplicated()]
-    co2_price = (
-        co2_price.reindex(n.snapshots).fillna(method="ffill").fillna(method="bfill")
-    )
+    co2_price = co2_price.reindex(n.snapshots).ffill().bfill()
 
     emissions = (
         n.generators.carrier.map(n.carriers.co2_emissions) / n.generators.efficiency

scripts/prepare_sector_network.py

@@ -2748,10 +2748,11 @@ def add_industry(n, costs):
         )
 
     domestic_navigation = pop_weighted_energy_totals.loc[
-        nodes, "total domestic navigation"
+        nodes, ["total domestic navigation"]
     ].squeeze()
     international_navigation = (
-        pd.read_csv(snakemake.input.shipping_demand, index_col=0).squeeze() * nyears
+        pd.read_csv(snakemake.input.shipping_demand, index_col=0).squeeze(axis=1)
+        * nyears
     )
     all_navigation = domestic_navigation + international_navigation
     p_set = all_navigation * 1e6 / nhours
@@ -3919,12 +3920,11 @@ if __name__ == "__main__":
 
         snakemake = mock_snakemake(
             "prepare_sector_network",
-            # configfiles="test/config.overnight.yaml",
             simpl="",
             opts="",
-            clusters="37",
-            ll="v1.0",
-            sector_opts="730H-T-H-B-I-A-dist1",
+            clusters="1",
+            ll="vopt",
+            sector_opts="",
             planning_horizons="2050",
         )